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Design of an Intrusion Detection System Based on Bayesian Networks

机译:基于贝叶斯网络的入侵检测系统设计

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This paper describes a structure of a standalone Intrusion Detection System (IDS) based on a large Bayesian network. To implement the IDS we develop the design methodology of large Bayesian networks. A small number of natural templates (idioms) are defined which make the design of Bayesian network easier. They are related to specific fragments of Bayesian networks representing the basic elements in reasoning about uncertain events. The idioms represent the graphical structure, without the probabilistic tables. The use of idioms speeds-up the development of Bayesian networks and improves their quality. Example network is constructed and examined. Such Bayesian network can represent an independent agent in a distributed system. Results are promising since with very limited computation and low sensitivity to the quality of prior knowledge, potentially dangerous situations are successfully detected and classified.
机译:本文介绍了一种基于大型贝叶斯网络的独立入侵检测系统(IDS)的结构。为了实施IDS,我们开发了大型贝叶斯网络的设计方法。定义了少量自然模板(惯用语),这使贝叶斯网络的设计更加容易。它们与贝叶斯网络的特定片段有关,这些片段代表了不确定事件推理中的基本元素。习惯用语表示图形结构,没有概率表。使用习语可以加快贝叶斯网络的发展并提高其质量。示例网络的构建和检查。这样的贝叶斯网络可以代表分布式系统中的独立代理。结果是有希望的,因为通过非常有限的计算和对先验知识质量的低敏感性,可以成功地检测和分类潜在的危险情况。

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